1. Field of the Invention
This invention relates to the detection of a significant cognitive response to relevant stimuli and more specifically to the detection and classification of instantaneous changes in pupil response as a correlate to cognitive response.
2. Description of the Related Art
A person's cognitive responses may be monitored to study human neurophysiology, perform clinical diagnosis and to detect significant responses to task-relevant or environmental stimuli. In the latter, the detection of such a response may be fed back or used in some manner in conjunction with the task or environment. The detection of a significant cognitive response does not classify the stimulus but generates a cue that the operator's neurophysiology has responded in a significant way. Various techniques for monitoring cognitive responses include electroencephalography (EEG), pupil dilation and function near IR spectroscopy (FNIRS), each of which has been correlated to changes in neurophysiology.
Pupil response provides a direct window that reveals sympathetic and parasympathetic pathways of the autonomic division of the peripheral nervous system. Task-evoked pupil dilations are known to be a function of the cognitive workload and attention required to perform the task. It has long been known that the pupil dilates in response to emotion evoking stimuli. Thus, cognitive task related pupillary response provides a modality that can be used to detect significant brain responses to task-relevant stimulus. Measurements of pupil dilation include averaging procedures, differencing of adjacent observations and smoothing techniques.
U.S. Pat. No. 6,090,051 suggests subjecting a subject's pupillary response to wavelet analysis to identify any dilation reflex of the subject's pupil during performance of a task. A pupillary response value is assigned to the result of the wavelet analysis as a measure of the cognitive activity. Wavelet analysis employs a mother wavelet selected from the Daubechies family of wavelets, Symlet wavelets, Coiflet wavelets, Morlet wavelets, the Battle-Lemarie family of wavelets and the Chui-Wang family of wavelets. The mother wavelet is applied iteratively to decompose the pupillary response into orthogonal transformations of the response at different frequencies or scale, each of which can be analyzed and interpreted.
The wavelet is a form of “matched filter” designed to detect specific high-frequency patterns of the signal under specific environmental conditions e.g. a subject performing specific tasks in a controlled environment. As such the wavelet is not robust to variations in stimuli or changes in environmental conditions e.g. noise. De-noising techniques do not fully address this issue. Furthermore, wavelet analysis makes a commitment to the high-frequency properties of a signal and lacks an ability to capture other qualitatively important measures of the pupil dilation behavior. Wavelet analysis is a complex non-linear calculation that does not lend itself to simple, fast hardware implementations.